With the increasing use of multimedia in recent years, there has been a need to process large volumes of information including video information. Storage devices of increased capacity are also needed for recording such information. In the field of storages for high quality video information in particular, a capacity exceeding that of the current DVDs (Digital Versatile Disks) is desired of the storage devices. Increasing of the capacity of optical disk apparatuses or HDD units necessitates raising of the recording density. With the recording density improved, it has become an important challenge to reduce an error rate and ensure the reliability. Approaches that have been made toward such an important challenge in terms of optical disks are broadly classified into three types: medium composition approaches, optical approaches, and signal processing approaches. The following description will deal primarily with the signal processing approaches.
In the optical disk, the disk medium is irradiated with a laser beam that is focused by an optical element, and information is detected from the brightness level or polarization of the reflected light. The focused beam spot is finite, and a smaller diameter of the beam spot allows performing of recording and reproducing with a higher density. Optical approaches have thus been employed to reduce the beam spot. The spot diameter is inversely proportional to the NA (Numerical Aperture) of the objective lens and is proportional to the wavelength λ of the laser beam. The spot diameter can thus be made smaller by increasing the NA and decreasing the λ.
A higher NA, however, leads to a shallower depth of focus, whereby the distance between the disk surface and the lens needs to be narrowed. There is thus a limit in the size of NA. The laser wavelength has been on the decrease from an infrared laser (λ=780 nm) for CD, via a red laser (λ=650 nm) for DVD to a blue laser (λ=405 nm) for next-generation DVD. Short-wavelength lasers, however, have such challenges as to achieve stability during high output-power lasing and a longer life. There is thus a limit in reducing the wavelength.
An MTF (Modulation Transfer Function), which is the frequency characteristic of the transfer channel between the optical head and the disk medium, appears as an LPF (Low-Pass Filter) which drops in gain at high frequencies, due to a finite beam spot thereof. Rectangular waves, if recorded, will thus be reproduced with obtuse waveforms. Besides, at an increased recording density, a waveform to be read at a specific time instant can interfere with those of other time instants to cause intersymbol interference. The intersymbol interference makes it difficult to reproduce shorter recorded marks of a specific length or less. If recorded marks are longer, on the other hand, a lower frequency of the output of phase information for extracting a synchronizing clock may cause a loss of synchronization. The mark length therefore needs to be limited to a certain length or less. From the foregoing reasons, data to be recorded on an optical disk is coded for a signal processing approach. The coding often uses RLL code (Run Length Limited code) which limits the distance of code inversion. Examples include ETM (Eight to Twelve Modulation), EFM (Eight to Fourteen Modulation), (1,7) RLL, and 8/16 code. Of these, the EFM modulation code which is used in CD and the 8/16 modulation code which is employed for DVD have a minimum run length of 2 (d=2). The (1,7) RLL and ETM modulation code have a minimum run length of 1. As described in Non-Patent Literature-1, ETM is (1,10) RLL code with a coding rate of ⅔ which is the same as that of (1,7) RLL. ETM is characterized by the limitation on the number of consecutive shortest marks and the performance for compressing DC (Direct Current) components.
There is a technology referred to as waveform equalization. The waveform equalization is to insert an inverse filter for eliminating intersymbol interference, thereby lowering the error rate. The equalization suppresses intersymbol interference by enhancing the high-frequency band components of the reproduced signal, whereas it also enhances the high-frequency band components of noise and sometimes degrades the SNR (Signal to Nose Ratio) of the reproduced signal. The SNR degradation caused by the waveform equalization is a primary factor of errors in detected data at an increased recording density in particular. PR (Partial Response) equalization is a technique of waveform equalization such as causes known intersymbol interference on purpose. The PR equalization does not enhance high-frequency components and can thus suppress SNR degradation.
Among effective techniques of detection is a maximum likelihood detection technique. The technique is to select a time series pattern, from among all possible time series patterns, that provides a minimum mean square of errors with respect to a data string that is known to make certain state transitions, thereby improving the detection performance. It is difficult to perform the foregoing processing on an actual circuit, however, in terms of circuit scale and operating speed. Maximum likelihood detection is thus usually performed by performing path selections asymptotically, using an algorithm referred to as Viterbi algorithm. The information detection using the maximum likelihood detection is referred to as Viterbi decoding or Viterbi detection.
A detection technique that combines the foregoing PR equalization with the Viterbi detection is referred to as a PRML (Partial Response Maximum Likelihood) technique, which can perform data detection with a kind of error correction. The reproduced signal is subjected to a correlation in the direction of time by the PR equalization. A data series that is obtained by sampling the reproduced signal therefore represents certain state transitions alone. Errors in the detected data can be reduced by comparing such limited state transitions with the data series of the actual reproduced data including noise and selecting most likely state transitions. A PRML detection technique using ETM code and a PR(1,2,2,2,1) channel is described in Non-Patent Literature-2. The technique can provide a wide detection margin during high-density recording and reproducing.
To improve the detection performance by Viterbi detection, the frequency characteristics of the reproduction channel need to coincide with certain PR equalization characteristics. PR equalization characteristics as close to those of the reproduction channel as possible are thus selected. Here, a waveform equalizer is typically used to correct the frequency characteristics of the reproduction channel so that the frequency characteristics coincide with specified PR characteristics. An automated equalization or adaptive equalization technique is a technology to adaptively correct the time degradation of the signal for improved detection performance Non-Patent Literature-3 describes adaptive equalization algorithms of sequential type. The Zero Forcing algorithm, the Mean Square algorithm, and the like are commonly used in particular. The adaptive equalization technology is highly effective because it eliminates the need for an initial adjustment to the apparatus.
Description will now be given of operation of the Viterbi detection. FIG. 8 illustrates the state transitions of a signal xn that is a DVD-reproduced signal which is sampled in synchrony with the channel clock, followed by PR(1,2,2,1) equalization. The numerals that accompany the branches extending from the six states represent ideal sample values. For example, in an area where a 4T space (T is the clock cycle) and a 4T mark occur in succession, the state changes such as S0→S1→S3→S7→S7→S6→S4→S0→S0→S1→ . . . as illustrated in FIG. 8. Ideally, xn assumes −3, −2, 0, 2, 3, 2, 0, −2, −3, −2, . . . . In fact, however, the xn assumes the values of, e.g., −2.9, −1.9, 0.1, 1.7, 2.9, 0.2, −1.6, −2.9, −2.1, . . . due to noise and other factors. The recording code employed for DVD is limited to a minimum run length of 2, and such paths as S3→S6 and S4→S1 do not exist.
Now, it is assumed that Gaussian noise is superposed on xn, and, rn assumes any of five reference levels {±3, ±2, 0}. Here, the maximum likelihood detection is to find out rn that minimizes Σ(xn−rn)2. Since it is difficult to compare all the combinations in real time, however, the Viterbi algorithm performs the rn calculations in succession.
FIG. 9 is a diagram illustrating the state transitions of FIG. 8 developed on the time axis, which is referred to as a trellis diagram. Referring to the diagram, it can be seen that the value of xn is constrained by previous and following values. PRML uses the constraint condition to improve the accuracy of identification. In FIG. 9, there are points where a plurality of paths are input, such as the states S0 and S7. If a certain condition is applied to the state transitions of FIG. 9 to select a single path from a plurality of paths that make the same state transitions, then the trellis diagram shown by a solid line in FIG. 10 is obtained. The broken lines represent a plurality of paths that are not selected. From the trellis diagram of FIG. 10, it is represented that the paths can be traced back from the respective states at time instant “n” to the past to reach a path merge where the paths converge into one. The information before the merged time instant is settled by the path merge thus obtained.
To select a single path from among a plurality of paths, there is introduced an index of probability referred to as metric. The probability Pan for a state Sa to be assumed at time instant n will be referred to as path metric. The square of a difference between xn and a reference level r will be defined as branch metric bn(r). The branch metric is expressed by the following equation-1:bn(r)=(xn−r)2;  (1)The reference level r is determined from the input signal xn of that time.
The path metric is a summation of branch metrics from the past, and indicates a higher probability if its value is smaller. Referring to FIG. 8, the state one clock (1T time) before the state S1 is always the state S0. A path metric P1n is thus given by adding the branch metric bn(−2) at the current time to the path metric P0n-1 of the state S0 that is one clock earlier. Thus,P1n=P0n−1+bn(−2).  (2)Likewise, P3n, P4n, and P6n are given by the following formulas:P3n=P1n-1+bn(0);  (3)P4n=P6n-1+bn(0);  (4) andP6n=P7n-1+bn(2).  (5)
P0n is calculated by the following way. The state one clock before the state S0 is S0 or S4. The state S0 has two paths. Here, the path metrics of the two paths are compared to select a path of smaller value. Assuming that Min[a,b] is a function to select the smaller value between “a” and “b”:P0n=Min[P0n-1+bn(−3),P4n-1+bn(−2)].  (6)Likewise, P7n is defined by the following equation-7:P7n=Min[P7n-1+bn(3),P3n-1+bn(2)].  (7)
The path metrics are updated and path selections are made at each time, whereby each state has a single path input. Such paths are sequentially traced back to the past, and beyond a certain time the paths merge to settle the information. Note that equations-6 and -7 have only to be capable of comparing the path metrics in magnitude. Since the term xn2 in bn(r) is common between all the path metrics, the branch metrics may be given by the following equation, in which case there is an advantage that the circuit can be simplified:bn(r)′=r2−2rxn.
The foregoing processing is usually performed in units of the channel clock, and a high speed processing is thus needed. For example, an 8×-speed DVD has a channel clock frequency of over 200 MHz, and the foregoing processing is thus typically performed by a dedicated circuit. FIG. 11 illustrates the configuration of a Viterbi detector. A path-metric calculation circuit 11 has the functions of adding a path metric and a branch metric, comparing path metric values, and selecting a path based on the result of comparison. Using the initials of the functions, the path-metric calculation circuit 11 is referred to as ACS circuit. The Viterbi detector includes at least the ACS circuit 11, a branch-metric generation circuit (BMG circuit) 10 which is intended to calculate branch metrics, and a memory (MEM) 13 which is intended to store path-select information and is referred to as path memory. In Viterbi detection, paths can be merged if the memory length is long. With a memory of finite length, some input signals may fail to be merged. In view of this possibility, the Viterbi detector in FIG. 11 includes a maximum-likelihood-path selection circuit (SEL) 14 that searches for a path having the minimum value among a plurality of path metric values and outputs the information thereof.
In the PRML detection, it is known that even a signal that has too low SNR to be detected by level detection at all can be detected by using a Viterbi detector so long as the signal level distribution after adaptive equalization is close to a normal distribution with respect to each reference level. This condition mostly corresponds to such cases as when recorded marks have superior quality and yet high jitter or high intersymbol interference, when a disk tilt occurs, and when reproduction is performed in a defocused state.
The PRML detection system can sometimes fall behind the conventional level detection system in performance, however, if marks are recorded on the disk in imperfect shapes mainly because of the control of recording power. FIG. 12 illustrates the reproduced waveform of a long mark (14T) with waveform distortion. The waveform corresponds to the reproduced waveform of a mark that is formed by a recording strategy such that the recording power decreases in the center of the long mark. With the level detection system, it is possible to detect the 14T from the foregoing waveform without a problem. The Viterbi detector, however, sometimes selects the path that is represented by the dotted line in the chart because of the decrease in amplitude. Here, the Viterbi detector can make an erroneous decision that the 14T mark is a 6T mark+a 3T space+a 5T mark, considering the low amplitude portion in the center of the long mark as the 3T space.
The Viterbi detection uses path metrics to determine the likelihood of the continuous waveform pattern as described above. Assuming that each sample point (solid circle) in FIG. 12 is xi and a string of ideal values of possible data path is ri, a path metric Pn at time instant n can be expressed by the following equation:Pn=Σi=1,n(xi−ri)2  (8)
Taking a span of six times, a path metric Pn′ with the long mark as ideal values and a path metric Pn″ with the 3T space as ideal values are expressed by the following respective equations:Pn′=(xn−3)2+(xn-1−3)2+(xn-2−3)2+(xn-3−3)2+(xn-4−3)2+(xn-5−3)2;  (9) andPn″=(xn-2)2+(xn-1−0)2+(xn-2+2)2+(xn-3+2)2+(xn-4−0)2+(xn-5−2)2.  (10)
If Pn′<Pn″, there is determined to be a long mark. If the input waveform is distorted, for example, like (xn-5, xn-4, xn-3, xn-2, xn-1, xn)=(1.8, 1.0, 0.5, 0.5, 1.0, 1.9), however, Pa′=23.15 and Pn″=14.55. That is, Pn′>Pn″. In this case, the long-mark path is not selected and there occurs an erroneous decision that there are a 6T mark+a 3T space+a 5T mark.
The level detection is a conventionally-used technique and has been employed for many optical disk drives. Reproduction compatibility with disks that are recorded by the conventional drives is indispensable even for optical disk drives that incorporate the Viterbi detection that has come into use recently. Although the PRML-based detection can be expected to improve the reproducing performance, there is the problem that the PRML detection may fall behind the threshold detection in performance when detecting a reproduced signal of high nonlinearity, such as when the recorded marks are imperfect.
Patent Publication-1 describes a technology for avoiding the foregoing problem. FIG. 13 illustrates the configuration of the apparatus described in Patent Publication-1. According to the technology, recorded data on an optical disk medium 50 is converted into an electric signal through an optical head 51 and corrected in frequency characteristics by a waveform equalizer 52 before being sampled by an A/D converter 53. The sampling clock here is the channel clock that a PLL 55 generates from the signal for which the range of DC variation at low frequencies is suppressed by an offset compensator 54. The output of the offset compensator 54 is input to a PRML detection system which includes a PR equalizer 56 and a maximum likelihood decoder 59, and to a binary discriminator 57 of a level discrimination system. The results of the two types of detection are input to a selection means 60, and either one of them is output. A mark-distortion-factor measurement means 58 calculates the waveform distortion factor of the output of the PR equalizer 56. Based on the distortion factor, the selection means 60 outputs the result of level detection if the distortion is higher. If the distortion ratio is lower, on the other hand, the selection means 60 outputs the result of PRML detection. This makes it possible to obtain a reproducing quality that is hardly influenced by mark distortions.    Patent Publication-1: JP-2005-93033A    Non-Patent Literature-1: Kinji Kayanuma, et al., “Eight to Twelve Modulation Code for High Density Optical Disk,” International Symposium on Optical Memory 2003, Technical Digest pp. 160-161, Nov. 3, 2003    Non-Patent Literature-2: Ogawa, Honma, et al., “Development of HD DVD drive technology (Recording technology),” ITE TECHNICAL REPORT VOL. 28, NO. 43, PP. 17-20, MMS2004-38, CE2004-39 (JULY 2004)    Non-Patent Literature-3: Shuzo Saito, et al., “Fundamentals of Modern Information Communications,” Ohm-sha, Dec. 20, 1992, pp. 212-217
The technique described in Patent Publication-1 includes switching to threshold detection if the mark distortion factor is higher. The detection performance higher than that of the level detection is therefore not available in spite of the implementation of PRML. The technique also involves the two detection systems and the special circuit for determining the distortion factor, with a result of an increase in the circuit scale and power consumption.